Additional Information
As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.
This is a high-impact Principal Product Manager - Tech role within Amazon Connect Decisions team. Amazon Connect Decisions a standalone agentic AI system designed to transform how customers manage supply chain operations. Our vision is to enable AI teammates (or agents) to help companies achieve best-in-class decisioning and planning capabilities. As a 0-to-1 product approaching General Availability, you'll join a startup-like environment building the most robust and agentic SaaS solutions serving external customers in the rapidly growing Supply Chain Planning market.
As the Principal PMT for Demand Intelligence (DI), you are responsible for the complete product lifecycle and P&L for this critical capability. You'll define the Ideal Customer Profile (ICP) specifically to your use case, collaborate with Go-To-Market teams to identify and win the right customers, and build products that genuinely meet customer needs. This role demands end-to-end ownership spanning use case definition, UX/Planning Hub experience, onboarding/configuration workflows, intelligence tooling, demand intelligence agents, ML forecasting models, adaptive learning systems, success metrics, and pricing strategy. You'll serve as the domain expert with deep knowledge of demand planning, forecasting, demand sensing, demand shaping, rapid response planning, metrics measurement, product lifecycle forecasting (NPI and EOL), demand plan exceptions, sales and operations planning, financial planning, collaborative planning processes. Additionally, you'll bring expertise in agentic AI experiences, understanding how to design autonomous AI agents that collaborate with human planners, enable continuous learning, and deliver intelligent recommendations through conversational interfaces.
Key job responsibilities
1. P&L Ownership: Responsible for the complete P&L responsibility for Demand Intelligence, including revenue targets, pricing strategy, and business case development across customer segments (Basic, Intermediate, and Sophisticated enterprises)
2. Product Vision, Strategy, and Roadmap: Define and champion the product vision while also owning the near-term product launch decisions and strategy. Define and execute the product strategy across five strategic pillars: (1) Accurate Forecasts, (2) Accelerated Time to Forecast Acceptance, (3) Feature Parity for Demand Planning Workflows, (4) Integrated Demand and Supply Planning, and (5) Performance at Scale
3. Customer-Centric Product Development: Lead customer discovery, beta programs, and feedback loops to continuously refine the product. Work backwards from customer needs, translate to actionable product requirements to deliver business outcomes for customers.
4. Agentic AI Innovation: Drive the development of AI-first capabilities including demand planner agents, conversational planning agents, 21+ intelligence tools, and human-in-the-loop (HITL) systems that enable continuous learning and adaptation
5. Cross-Functional Leadership: Partner closely with engineering (SDEs/SDMs), data science, UX, and Go-To-Market teams to deliver on ambitious roadmap commitments. Write detailed Business Requirements Documents (BRDs) and drive execution
6. Market Positioning: Define, refine, and expand ICP segmentation based on technology maturity (not just company size), enabling GTM teams to focus on winnable customers while sequencing product capabilities appropriately
7. Technical Product Excellence: Own complex technical decisions around ML model selection, model ensembling, model optimization metrics, model training frameworks (including SCOT and Chronos Foundation Models), feature engineering, data enrichment, hierarchical forecasting, and system integrations with third-party platforms
8. Success Metrics & Analytics: Define and track key metrics including forecast accuracy improvement (MAPE/WAPE), time to forecast acceptance, feature adoption, customer satisfaction, and business outcomes (inventory optimization, service level improvements)
Amazon Development Center U.s · Seattle, WA